Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Paul Smolensky
Since
Specialization
Citations
This map shows the geographic impact of Paul Smolensky's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Paul Smolensky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Smolensky more than expected).
This network shows the impact of papers produced by Paul Smolensky. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Paul Smolensky. The network helps show where Paul Smolensky may publish in the future.
Co-authorship network of co-authors of Paul Smolensky
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Smolensky.
A scholar is included among the top collaborators of Paul Smolensky based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Paul Smolensky. Paul Smolensky is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Palangi, Hamid, Paul Smolensky, Xiaodong He, & Li Deng. (2017). Deep Learning of Grammatically-Interpretable Representations Through Question-Answering.. arXiv (Cornell University).6 indexed citations
5.
Huang, Qiuyuan, Paul Smolensky, Xiaodong He, Li Deng, & Dapeng Wu. (2017). A Neural-Symbolic Approach to Natural Language Tasks.. arXiv (Cornell University).2 indexed citations
6.
Palangi, Hamid, Qiuyuan Huang, Paul Smolensky, Xiaodong He, & Li Deng. (2017). Grammatically-Interpretable Learned Representations in Deep NLP Models. Neural Information Processing Systems.1 indexed citations
7.
Smolensky, Paul. (2012). Symbolic functions from neural computation. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 370(1971). 3543–3569.14 indexed citations
Smolensky, Paul & Géraldine Légendre. (2006). Linguistic and philosophical implications. MIT Press eBooks.5 indexed citations
10.
Smolensky, Paul & Géraldine Légendre. (2006). The Harmonic Mind: From Neural Computation to Optimality-Theoretic GrammarVolume I: Cognitive Architecture (Bradford Books). The MIT Press eBooks.29 indexed citations
11.
Smolensky, Paul. (2005). An fMRI Study of the Effects of Memory and Goal Setting in a Risk Taking Task. eScholarship (California Digital Library). 27(27).1 indexed citations
Hale, John & Paul Smolensky. (2001). A Parser for Harmonic Context-Free Grammars. eScholarship (California Digital Library). 23(23).2 indexed citations
14.
Smolensky, Paul. (1996). On the comprehension/production dilemma in child language. Linguistic Inquiry. 27(4). 720–732.171 indexed citations
15.
Smolensky, Paul, et al.. (1993). Integrating connectionist and symbolic computation for the theory of language. Current Science. 64(6). 381–391.10 indexed citations
16.
Mozer, Michael C., et al.. (1993). Dynamic Conflict Resolution in a Connectionist Rule-Based System.. International Joint Conference on Artificial Intelligence. 1366–1373.3 indexed citations
17.
Mozer, Michael C., et al.. (1991). The Connectionist Scientist Game: Rule Extraction and Refinement in a Neural Network. eScholarship (California Digital Library).11 indexed citations
18.
Légendre, Géraldine, Yoshiro Miyata, & Paul Smolensky. (1990). Distributed Recursive Structure Processing. Neural Information Processing Systems. 47–53.5 indexed citations
Smolensky, Paul. (1983). Schema selection and stochastic inference in modular environments. National Conference on Artificial Intelligence. 378–382.48 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.